The previous articles talked about infrastructure but business and infrastructure go together. While describing generative AI and infrastructure to support AI models, cloud engineers who participate in new and upcoming business initiatives can bring their AI chops to contribute to proposals.

As with all aspects of writing, Generative AI can be helpful to write business proposals. AI has a transformative power in business and it only helps to remain competitive. The McKinsey Global Survey highlights the rapid adoption of generative AI, with one-third of organizations using it regularly. This article explains how to integrate generative AI into proposal writing.

Generative AI reasons like a human to generate content by mimicking human language patterns. The same models can be extended to music, images, designs and more. Specific actions can be automated with agents and made part of the flow so that the models can leverage that to enhance content. When a human drafts an article in solo mode, it might be usually 500 words per hour but with generative AI, this can be up to 2500 words per hour. It saves time in knowledge management, leading to higher proposal-win rates.

The way to unlock efficiency in bid writing, for example, is to leverage Generative AI to access and organize crucial information because models can learn the salience of various topics in the domain and predict what comes after say, a given topic. Brainstorming and thinking is still the forte of humans and for the near future. By combining both, writers can dedicate more time for creative approaches to their proposals while leveraging run-off-the-mill language and content for specific topics. This results in a more compelling proposal. Early adopters can outshine competitors and capture new opportunities. Emphasis must be on educating leadership about generative AI to harness its full potential and create a culture of acceptance within the organization.

As with any emerging technology, safety and security must be constantly assessed. If there is reason to believe that a suggestion in the generated content might not be true, a review will catch that. It is therefore necessary to watch out for hallucinations in the generated content as much as it is time-saving to leverage the points cited in the generated content that would have taken a while by itself. Care must also be taken to remove bias and make the data more inclusive for the AI models. This will improve the outcome of the research and the proposal. There are AI Standards to adhere to for fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. Vendors often use the term “Responsible AI” to demonstrate compliance to these principles.

The right tool for proposal writing also makes a difference. It should align with your purpose and be future-ready so that the full return on investment on AI can be unlocked. Since organizational needs evolve, continuously enhancing and refining the expectations from the tool also helps.

Proposal writing is an industry in itself. AI enhances stages for creative ideation, evidenced ideation, contextualized ideation, story-boarding, narrative structure creation, evidenced-winning prose evaluation, case study insertion, statistics insertion, “Tell me how” evidencing, incorporation of win themes, issues, and requirements, scoring criteria analysis, mega-extraction and mega-transformations and embedded semantic research. All of these can be used with slight modifications for bids & proposals, marketing, sales materials, thought leadership, internal communications, and public relations.

#codingexercise: CodingExercise-01-19-2025.docx